The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 14 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Knoop: Scaling Test-Time Compute Will Not Get Us to AGI
“And then there's a new story that's emerged over the last like five months, which is, oh, we're going to scale up this test time compute and that's going to get us to AGI. And I think what V two shows is that that's not quite either. We still need some structu…”
Knoop: Language models operate by memorization rather than solving novel patterns
“Language models. Generally working like a memorization style regime where they're right. Learning lots of data. They're able to apply it to very similar types of patterns that they've seen before, but not novel patterns. That's what RKGI shows.”
Knoop: ARC Saw No Progress Despite 50,000x Model Scaling
“Surprise that it basically hadn't, and not only hadn't been beaten, there'd basically been no progress in it which I thought was really fascinating given the fact that we've like scaled up these language model systems by almost like 50,000 times over the last,…”
Knoop: Pure LLMs Score 0% and o1 Scores 1% on ARC-AGI-2
“Pure LLM systems are scoring like zero percent now again on on arc B two single COT systems like R one and O one score like one percent.”
Knoop: AI agents will start working in 2025 due to ARC progress
“I actually think we're going to start to see agents start to work this year specifically because of progress on arc.”
Knoop: Startups just doing model training are lighting money on fire
“I think anyone who's like Just doing model training at this point is like lighting money on fire. If you really want to make a unique difference, especially if you're a small startup, like a founder, like you gotta go take an orthogonal approach. You gotta try…”
Knoop: Gary Marcus has been more right than wrong on deep learning
“I generally think he's been more right than wrong. I think if you like just take a limited five year view on this from 20, 20 up until 20, 20, end of 20, 24, you know, I think it was a generally right. Like he was making the right ideas.”
Knoop: Achieving AGI requires merging deep learning with program synthesis
“I actually don't think either is sufficient. I think some merger of the two is what's necessary to get to AGI.”
Knoop: AI intelligence benchmarks must measure compute efficiency, not brute force
“We do think that efficiency is actually a really, really important aspect of intelligence. You know, you can brute force your way up to intelligence, but we really do want to be shooting for like human targets and efficiency for this stuff.”
Knoop: People should still learn to code for technological leverage
“My hot take is, like, I guess, yes, you should still learn to code. Primarily because it's been, it gives you like leverage over technology today. And yeah, like I don't see that leverage over technology going away anytime soon, particularly if you want to wor…”
Knoop: AI Agent Failure Rates Make Unsupervised Automation Unviable
“Like, hey, I get the hype, but like, they just, they're not reliable enough yet. You know, they don't work two out of 10 times, and that just doesn't work for these unsupervised automation products.”
Knoop: ARC proves individuals can still advance frontier AI
“And I think arc shows that like, yeah, there actually are frontier problems. That are unsolved, that individual people and individual teams can actually make a difference on today.”
Knoop: Zapier never spent its $1M seed round from 2012
“It was about a million bucks back in 2012. We never spent the money. By the time we actually got the round closed, figured out who we wanted to hire, got the payroll started, like revenue had caught up. And so literally I think you could trace every dollar we …”
Knoop: OpenAI asked ARC Prize team to verify results on semi-private dataset
“Opening eye situation was a little different because they had reached out to us and said, Hey, we think we've got a really impressive result on the public eval set. And we'd like your help to verify. On the semi-private set, which is what we created that data …”